PLOS
open access
CC BY 4.0
Graph neural network-based risk stratification of prostate cancer using gene expression and SHAP interpretability
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Interpretable neural network for risk stratification and drug target discovery based on PBMC transcriptomes.#30538
- Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases.#9669
- Table 1_The role of molecular profiling for castration-resistant prostate cancer treatment and therapy development.docx#471743
- Artificial Intelligence Versus Conventional Methods for NCCN Risk Stratification in Localized Prostate Cancer (2020-2025): A Systematic Review.#392723
- A decision-oriented framework for genomic testing across the prostate cancer continuum.#421027
Record · ID 672172
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive